Sensing
coverage is a fundamental problem in wireless sensor networks. It reflects how
well the environment is monitored, and serves as a basis for applications such
as physical phenomenon or target detection, classification and tracking. Due to
the increasing diversity of sensor network applications, the concept of sensing
coverage includes a growing range of interpretations.

In this
work, we consider coverage problems involving two new characteristics of
emerging visual as well as mobile sensor networks. The solution approach to
both problems utilizes tools from optimization theory and algorithmic
complexity.

In the
first problem, we study power-efficient coverage by randomly deployed
directional sensors with tunable orientations on a set of discrete targets.
This problem arises, for example, in networks of visual surveillance sensors
(e.g. on-chip cameras with finite field of view). We consider centralized as
well as distributed solutions of this problem, and evaluate the properties of
the proposed solutions and algorithms in terms of providing coverage (minimizing
the number of targets missed) while maximizing network lifetime through
mathematical analysis and extensive simulations. Furthermore, the topic has
interesting synergies with the research interest of collaborators in the
computer vision group from ECSE and CS.

In the
second problem, we consider a network of sensors whose mobility is controlled
by the designer (rather than random). The objective is to capture stochastic
events appearing at points of interest with a minimum target quality. While
mobile sensors cover more area over a period of time than the same number of
stationary sensors, the quality of coverage achieved by mobile sensors depends
on the velocity, mobility pattern and number of mobile sensors deployed and the
dynamics of the phenomenon being sensed. This research considers the gains
attained, if any, by mobile sensors over static sensors and the optimal motion
strategies for mobile sensors. Applications of these results span a wide array
of applications, from unmanned underwater vehicles to border control. Synergies
also exist here with the robotics group.

We also
considered the effect of packet loss on the quality of coverage in sensor
networks. This is important since packet loss can not be avoided due to the use
of wireless links. This issue has been considered in the context of a network
of geotechnical sensors for monitoring landslides developed in collaboration
with the Civil Engineering department (through NSF funding).